Adaptive synergies for a humanoid robot hand

Catalano, Manuel G.; Grioli, Giorgio; Serio, Alessandro; Farnioli, Edoardo; Piazza, Cristina; Bicchi, Antonio

doi:10.1109/humanoids.2012.6651492

Cited by 121 publications

(102 citation statements)

References 13 publications

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“…While load-controlled friction is very useful for grasping objects, it has two drawbacks: the squeezing normal force can crush delicate or deformable objects, and the normal force tends to push objects out of the grasp in the case where the gripper cannot reach at least halfway around the object. Examples of such grippers are numerous, including rigid and fully actuated ones [2]- [4], as well as more compliant, underactuated and back drivable grippers [5]- [7]. Extensive reviews are provided in [8], [9].…”

Section: Introductionmentioning

confidence: 99%

Grasping Without Squeezing: Design and Modeling of Shear-Activated Grippers

et al. 2018

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Abstract-Grasping objects that are too large to envelop is traditionally achieved using friction that is activated by squeezing. We present a family of shear-activated grippers that can grasp such objects without the need to squeeze. When a shear force is applied to the gecko-inspired material in our grippers, adhesion is turned on; this adhesion in turn results in adhesion-controlled friction, a friction force that depends on adhesion rather than a squeezing normal force. Removal of the shear force eliminates adhesion, allowing easy release of an object. A compliant shearactivated gripper without active sensing and control can use the same light touch to lift objects that are soft, brittle, fragile, light, or very heavy. We present three grippers, the first two designed for curved objects, and the third for nearly any shape. Simple models describe the grasping process, and empirical results verify the models. The grippers are demonstrated on objects with a variety of shapes, materials, sizes, and weights.

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Section: Introductionmentioning

confidence: 99%

Grasping Without Squeezing: Design and Modeling of Shear-Activated Grippers

et al. 2018

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“…Grasping synergies is an efficient concept to simplify control of high-dofs hands inspired by human grasping. Whether the synergy is integrated in the mechanical design of sub-actuated hands [31] or simulated in software [32], it decreases the dimensionality of the control problem. However, synergy-based grasping strategies can also lead to unsuccessful grasps and they do not seek to maximize the contact surface.…”

Section: Grasping Under Uncertainty With Multiple Dofsmentioning

confidence: 99%

Multi-contact haptic exploration and grasping with tactile sensors

Sommer

Billard

2016

Robotics and Autonomous Systems

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Haptic exploration has received a great deal of attention of late thanks to the variety of commercially available tactile sensors. While the majority of previous works consider control of a single contact point at a time, we tackle simultaneous control of multiple contact points on several links. In addition, we use information from the existing tactile signals to increase the number of points in contact. We demonstrate the usefulness of this form of control to speed up exploration, scanning and to compliantly grasp unknown objects. Our controller requires to know only the parts of the robot on which it is desirable to make contact and does not need a model of the environment besides the robot itself. We validate the algorithm in a set of experiments using a robotic hand covered with tactile sensors and arm. In a grasping application, the active adaptation of the fingers to the shape of the object ensures that the hand encloses the object with multiple contact points. We show that this improves the robustness of the grasp compared to simple enclosing strategies. When combined with an exploration strategy, our multi-contact approach offers an efficient use of tactile sensors on the whole surface of robotic fingers, and enables the robot to perform a rapid exploration of complex, non convex shapes while maintaining low contact forces. It is robust to variation in the approach angle and to changes in the geometry and orientation of the object.

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“…These devices are based on mechanical systems using a number of motors [7][8][9][10] or on selfadapting devices using a single motor [11][12][13] .…”

Section: Introductionmentioning

confidence: 99%

A model for the grasping analysis of an underactuated finger driven by unextensible tendon

2016

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Abstract. A grasping analysis is presented of an underactuated finger driven by unextensible tendon. The finger itself is one of those of a mechanical prosthesis that was principally conceived as human prosthesis. After a brief description of the whole system constituted by the mechanical hand, the model to predict the behavior of the finger during the grasping is presented; then some examples of grasping are presented. The model can be useful for both the under-actuated finger design and for the prediction of the capabilities of the whole hand.

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Adaptive synergies for a humanoid robot hand

Cited by 121 publications

References 13 publications

Grasping Without Squeezing: Design and Modeling of Shear-Activated Grippers

Grasping Without Squeezing: Design and Modeling of Shear-Activated Grippers

Multi-contact haptic exploration and grasping with tactile sensors

A model for the grasping analysis of an underactuated finger driven by unextensible tendon

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